Clinical Presentation, Laboratory Findings, Complications, and Mortality of Influenza During the Epidemic of October 2019-February 2020 in Iran

Background: Influenza is one of the most important viruses and causes millions of infections and 290-600 thousands deaths annually. We aimed to evaluate the hospitalization rates due to complications caused by the influenza virus (pneumonia, seizures, sinusitis, otitis, myositis and encephalitis), the frequency of clinical signs, and laboratory findings in children under 15 years of age infected with Influenza.Methods: We conducted a cross-sectional study during the Influenza epidemic in Qom, Iran, from October 2019 to February 2020. Children under 15 years of age with the definitive diagnosis of influenza obtained by polymerase chain reaction (PCR) test were included.Results: Out of 1225 patients who referred to us with flu-like symptoms; 1172 patients were referred by the emergency department and our hospital clinic but 53 patients were referred to us by other paediatricians. 375 patients (30.61%) who had a positive PCR test result for influenza and suffered from complications caused by the virus were hospitalized.The number of male hospitalized patients was 231 (61.6% of hospitalized patients) and the number of female hospitalized patients was 144 (38.4% of hospitalized patients) respectively.The highest age range of patients with pneumonia was of 13 months to 3 years with a hospitalization rate of 36.41% and the lowest hospitalization rate was of 12 years to 15 years with a hospitalization rate of 0.84%.The most serious complication observed in patients caused by the influenza virus was pneumonia; with 17 cases (4.53%) reported.89.6% of patients had fever at the time of referral causing it to be the most common clinical symptom among patients. Cough ranked second with 76.8%.Lymphopenia and leukopenia was recognized as the most common laboratory findings with a frequency of 26.33% and 21.85%.Conclusions: Complications of influenza was not uncommon in children and affected a fifth of the patients. The influenza epidemic of October 2019- February 2020 imposed a heavy burden on our hospital and the learned lessons should be implemented to further assist the physicians in future influenza epidemic.

Simulation and forecasting of the influenza epidemic process using seasonal autoregressive integrated moving average model

Today's global COVID-19 pandemic has affected the spread of influenza. COVID-19 and influenza are respiratory infections and have several similar symptoms. They are, however, caused by various viruses; there are also some differences in the categories of people most at risk of severe forms of these diseases. The strategies for their treatment are also different. Mathematical modeling is an effective tool for controlling the epidemic process of influenza in specified territories. The results of modeling and forecasts obtained with the help of simulation models make it possible to develop timely justified anti-epidemic measures to reduce the dynamics of the incidence of influenza. The study aims to develop a seasonal autoregressive integrated moving average (SARIMA) model for influenza epidemic process simulation and to investigate the experimental results of the simulation. The work is targeted at the influenza epidemic process and its dynamic in the territory of Ukraine. The subjects of the research are methods and models of epidemic process simulation, which include machine learning methods, in particular the SARIMA model. To achieve the aim of the research, we have used methods of forecasting and have built the influenza epidemic process SARIMA model. Because of experiments with the developed model, the predictive dynamics of the epidemic process of influenza for 10 weeks were obtained. Such a forecast can be used by persons making decisions on the implementation of anti-epidemic and deterrent measures if the forecast exceeds the epidemic thresholds of morbidity. Conclusions. The paper describes experimental research on the application of the SARIMA model to the epidemic process of influenza simulation. Models have been verified by influenza morbidity in the Kharkiv region (Ukraine) in epidemic seasons for the time ranges as follows: 2017-18, 2018-19, 2019-20, and 2020-21. Data were provided by the Kharkiv Regional Centers for Disease Control and Prevention of the Ministry of Health of Ukraine. The forecasting results show a downward trend in the dynamics of the epidemic process of influenza in the Kharkiv region. It is due to the introduction of anti-epidemic measures aimed at combating COVID-19. Activities such as wearing masks, social distancing, and lockdown also contribute to reducing seasonal influenza epidemics.

PENGARUH WORK FROM HOME TERHADAP KINERJA KARYAWAN DI MASA PANDEMI COVID 19

Working from home (WFH) has been implemented at PT. Sakti Mandiri Gifari Makassar in order to investigate the impact of WFH on employee performance and employee performance procedures during the influenza epidemic. The descriptive quantitative methodologies were used in this study, and a sample of 113 respondents from PT. Sakti Mandiri Gifari Makassar was selected using a random sampling methodology for the study. On the basis of the findings of the descriptive statistical test analysis, the data validity test, and the regression analysis, it can be concluded that Work from Home (WFH) has a high link with employee performance (t = 4.757) and has a statistically significant effect (p = 0.000). As a result, in this analysis, we accept Ha and reject HO, which indicates that the WFH variable (X) has a statistically significant effect on the employee performance variable (Y).

About the bacterial flora with appendicitis. D. E. Hudacsek and F. Kerb 1er (Arch. F. Klin. Chir. Bd. 161. H. 3)

D. E. Hudacsek and F. Kerb 1er (Arch. F. Klin. Chir. Bd. 161. H. 3) examined 150 appendixes and, using the influenza epidemic, established that clinical observations speak for the existence of a connection in some cases between the influenza epidemic and the coming appendicitis.